Meraglim’s CEO Kevin Massengill shares his insight and thoughts regarding the Great Reset with Chris Blasi, CEO of Neptune-GBX Global Bullion Exchange. Critical topics include the fate of debt-based money, the inevitable road to war, worldwide financial destruction, and how to preserve wealth during these times.

A popular notion is that data-adaptive machine models are the nee plus ultra of modeling technology that will make human involvement in model-making obsolete. However, the scope of data-adaptive models is fundamentally limited by the scope of the data available to train them, which is necessarily restricted to historical and/or categorical data, and by the scope of model meta-structures that can be learned from these data.

The most powerful models in the world are those that incorporate human intuition and creativity in conjunction with algorithmic adaptivity. The widely popular and powerful model subclass of deep neural networks provides a perfect illustration of this point. Deep neural networks perform remarkably well on many pattern classification and analysis problems, but their meta-structure did not emerge autonomously from algorithmic ingestion of voluminous data sets.

Instead, it was created by human experts who observed the meta-structure of the brain and then (crudely) mimicked it in algorithmic implementations. Thus is generally the case with all approaches to modeling, and the more conceptually complex the domain of interest, the more vital is the incorporation of human expertise into the creation of the model meta-structure.

Once this is done, the algorithms then can be unleashed to perform their computationally intensive inferences within such a structure. But to imagine that the algorithms themselves are capable of the teleological feats needed to generate their own meta-structure without human involvement represents the triumph of hype over real-world experience with models.

What if you could see into the future? What if your investment strategy relied on advance knowledge of how world markets and business trends would play out? Well, it may sound like science fiction, but one team is making it a reality. The experts at Meraglim™ have created a predictive analytics system using AI technology to forecast market moves months ahead of time.
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Joining us today is Meraglim™ Founder & CEO, Kevin Massengill. He’s a former Army Ranger qualified officer, a successful businessman, and an investment visionary. His data-driven perspective on investment and market predictions is changing the game. He’s here to share with us more about predictive analytics and offer some key insights on developing investment opportunities.

The article I will share with you today was in the works for over a year. I sat down to write it several times, and every time, until the last time, I walked away with just an incomplete paragraph or two. Just like any article about today’s global economy, it is an open-ended article. When I shared a draft with my father, his response was, “So What?” I answered … see the answer in the P.S. section.

When I was growing up in the Soviet Union, our local grocery store had two types of sugar: The cheap one was priced at 96 kopecks (Russian cents) a kilo and the expensive one at 104 kopecks. I vividly remember these prices because they didn’t change for a decade. The prices were not set by sugar supply and demand but were determined by a well-meaning bureaucrat (who may even have been an economist) a thousand miles away. If all Russian housewives (and househusbands) had decided to go on an apple pie diet and started baking pies for breakfast, lunch and dinner, sugar demand would have increased but the prices still would have been 96 and 104 kopecks. As a result, we would have had a shortage of sugar — a very common occurrence in the Soviet era.

In a capitalist economy, the invisible hand serves a very important but underappreciated role: It is a signaling mechanism that helps balance supply and demand. High demand leads to higher prices, telegraphing suppliers that they’ll make more money if they produce extra goods. Additional supply lowers prices, bringing them to a new equilibrium. I am slightly embarrassed as I write this, because you may confuse me for an economist — I am not one. But this is how prices are set for millions of goods globally on a daily basis in free-market economies.

In the command-and-control economy of the Soviet Union, the prices of goods often had little to do with supply and demand but were instead typically used as a political tool. This in part is why the Soviet economy failed — to make good decisions you need good data, and if price carries no data, it is hard to make good business decisions.

When I left Soviet Russia in 1991, I thought I would never see a command-and-control economy again. I was wrong. Over the past decade our global economy has started to resemble one, as the well-meaning economists running central banks have been setting the price for the most important commodity in the world: money. Interest rates are the price of money, and the daily decisions of billions of people and their corporations and governments should determine them. Like the price of sugar in Soviet Russia, interest rates today have little to do with supply and demand (and thus have zero signaling value).

For instance, if the Federal Reserve hadn’t bought over $2 trillion of U.S. debt by late 2014 when U.S. government debt crossed the $17 trillion mark, interest rates might have started to go up and our budget deficit would have increased and forced politicians to cut government spending. But the opposite has happened: As our debt pile has grown, the government’s cost of borrowing has declined.

The consequences of well-meaning (but not all-knowing) economists setting the cost of money are widespread, from the inflation of asset prices to encouraging companies to spend on projects they shouldn’t. But we really don’t know the second, third and fourth derivatives of the consequences that command-control interest rates will bring. We know that most likely every market participant was forced to take on more risk in recent years, but we don’t know how much more because we don’t know the price of money.

Quantitative easing: These two seemingly harmless words have mutated the DNA of the global economy. Interest rates heavily influence currency exchange rates. QE by the U.S. and European Union caused the price of the Swiss franc to jump 15 percent in one day in January 2015, and the Swiss economy has been crippled ever since.

Americans have a healthy distrust of their politicians. We expect our politicians to be corrupt. We don’t worship our leaders (only the dead ones). The U.S. Constitution is full of checks and balances to make sure that when (often not if) the opium of power goes to a politician’s head, the damage he or she can do to society is limited.

Unfortunately, we don’t share the same distrust for economists and central bankers. It’s hard to say exactly why. Maybe we are in awe of their Ph.D.s. Or maybe it’s because they sound very smart and at the same time make us feel dumber than a toaster when they use big econ terms like “aggregate demand” or “degenerate equilibrium” (okay, I made up the last one). Or simply because they often look just like our well-meaning grandparents. For whatever reason, we think they possess foresight and the powers of Marvel superheroes.

Warren Buffett — the Oracle of Omaha himself — admitted that he doesn’t know how the QE experiment will end. And if you think well-meaning economists running central banks know, you may have another think coming.

Alan Greenspan — the ex-pope of the Federal Reserve — in a 2013 interview with the Wall Street Journal said that he “always considered [himself] more of a mathematician than a psychologist.” But after the financial crisis, and the criticism he received for contributing to the housing bubble at the core of it, Greenspan went back and studied herd behavior, with some surprising results. “I was actually flabbergasted,” he admitted. “It upended my view of how the world works.”

Just as the well-meaning economist of the Soviet Union didn’t know the correct price of sugar, nor do the good-intentioned economists of our global central banks know where interest rates should be. Even more important, they can’t predict the consequences of their actions.

P.S. If Martian economists paid a visit to Planet Earth and surveyed our global economy, they’d form a very different view of its true health than most earthlings have. See, Martians wouldn’t be influenced by the positive feedback loop generated by a seven-year bull market in stocks. The “low unemployment” numbers spat out by government agencies and touted by presiding politicians would also have little influence on them. They’d look at the percentage of people employed in the US, which is 3.5% below the 2007 high, and understand that true unemployment is probably double the official number.

The Martians would not be swayed by the calmness and confidence exuded by central banks economists. They’d see that the global economy is barely producing modest growth while government debt is on the rise and interest rates are mostly at zero or even less.

After they studied our wild- and not-so-wild life they would conclude that the most superior and resilient living species on Earth is the cockroach, which seems to survive anything. If the Martians were to set themselves the task of constructing a stock portfolio that would perform well under the tumultuous market conditions that pertain on the Earth today, they would of course try to model the portfolio after that incredible insect. This is what I told my father.

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